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Jupyter for Data Science

You're reading from Jupyter for Data Science Exploratory analysis, statistical modeling, machine learning, and data visualization with Jupyter

Product type Paperback

Published in Oct 2017

Publisher Packt

ISBN-13 9781785880070

Length 242 pages

Edition 1st Edition

Languages

Python

Tools

Jupyter

Concepts

Data Analysis

Author (1):

Dan Toomey

View More author details

Table of Contents (11) Chapters

Preface

1. Jupyter and Data Science FREE CHAPTER

2. Working with Analytical Data on Jupyter

3. Data Visualization and Prediction

4. Data Mining and SQL Queries

5. R with Jupyter

6. Data Wrangling

7. Jupyter Dashboards

8. Statistical Modeling

9. Machine Learning Using Jupyter

10. Optimizing Jupyter Notebooks

Jupyter and Data Science

The Jupyter product was derived from the IPython project. The IPython project was used to provide interactive online access to Python. Over time it became useful to interact with other programming languages, such as R, in the same manner. With this split from only Python, the tool grew into its current manifestation of Jupyter. IPython is still an active tool available for use.

Jupyter is available as a web application for a wide variety of platforms. It can also be used on your desktop/laptop over a wide variety of installations. In this book, we will be exploring using Jupyter from a Windows PC and over the internet for other providers.

You have been reading a chapter from

Jupyter for Data Science

Published in: Oct 2017

Publisher: Packt

ISBN-13: 9781785880070

© 2017 Packt Publishing Limited All Rights Reserved

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Authors (1)

Toomey

Toomey

Dan Toomey has been developing application software for over 20 years. He has worked in a variety of industries and companies, in roles from sole contributor to VP/CTO-level. For the last few years, he has been contracting for companies in the eastern Massachusetts area. Dan has been contracting under Dan Toomey Software Corp. Dan has also written R for Data Science, Jupyter for Data Sciences, and the Jupyter Cookbook, all with Packt.

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